Types Of Players Research Articles

An Optimal Decision Method for Intrusion Detection System in Wireless Sensor Networks With Enhanced Cooperation Mechanism

When it comes to selecting an optimal defense strategy for an intrusion detection system of a wireless sensor network, such challenges as those brought about by the diversification of the attack methods and the expanded database of the attack patterns have to be dealt with. To overcome those challenges, this paper combines realistic bounded rationality with the incomplete information of the attack-defense players by employing evolutionary game theory as a tool. Firstly, an attack-defense evolutionary game model considering three types of population, in which attackers are subdivided by the source of the threat into external attackers and selfish nodes, is proposed. The sets of player types and the game strategies in our model can be extended from 2×2 to n× m × l. The sensitivity of the evolutionary population to similar strategies, which reflects the efficiency change in the multi-agent learning process, is depicted by a replicator dynamic equation especially optimized for this purpose by the introduction of an enhanced cooperation mechanism. In essence, an optimal defense strategy selection algorithm is provided by calculating the evolutionary stable equilibrium and a description of the evolutionary trajectory of the players over time is obtained. Moderate security and proactive defense in the form of support decisions have been provided by our method for wireless sensor networks. Experimental results have verified the validity of our method. Moreover, the optimized algorithm has solved the problem that an excessively large database of attack patterns affects the speed of switching to the optimal defense decision strategy and the learning efficiency of the evolutionary game replicator dynamic mechanism is not fast enough.

Upper body injuries and Key Performance Indicators in professional basketball players

ntroduction: Upper body injuries are less common than lower body injuries in basketball, but there is still a lack of knowled-ge about the relationship among their occurrence and the performance profile of professional basketball players. This study aimed to analyse the relationships between upper-body injuries and Key Performance Indicators (KPIs) of basketball players. Material and method: Statistical variables of 554 professional basketball players (age: 26.97±4.86 years, height: 199.23±8.80 cm, minutes per season: 441.18±301.41) in Spanish ACB (Asociación de Clubes de Baloncesto) professional competition were analysed for two seasons (2012-13 and 2013-14). Besided, injury reports were registered and injuries were categorized with OSICS-10 classification. The players who played the most minutes during the season were more likely to suffer lumbar spine, head, wrist, and hand injuries. The players injured in the thoracic spine obtained a better average in steals per minute. The players injured in the head or the elbow had better +/- performance per minute. The players injured in the neck had better means per minute in received fouls, free throws made and attempted. Results: The players injured in the lumbar spine had better means, per minute played, in assists, probably by their continuous column twists to protect the ball with the body to avoid bumps. Players injured in the shoulder had more blocked shots per minute than those not injured, probably because the realization of a block involves a shoulder flexion and rotation. It would be interesting to carry out a specific follow-up in this type of player, for this type of injury. This information could be helpful to improve injury prevention with the use of KPIs of basketball.

Sustainable society based on social gamification using Nova Empire ecology mining

In recent years, with the development of social app, the Internet has created a different interactive mode from the previous daily life, which makes the development of society gradually presents the trend of “gamification”. “Social gamification” makes the life systematically integrated into the competition activities. Therefore, we propose a new idea for the realization of a sustainable society under the trend of “social gamification” by combining strategy game ecology mining for the first time. Specifically, we use big data mining to analyze the attributes of the smurf (subsidiary account), and then extract discriminative features and compute a score for each attribute using machine learning, which could accurately locate all the smurf in the game. By banning the smurf, the game ecology is optimized to improve the player’s game experience. Meanwhile, this paper proposes appropriate operation strategies for players at different stages based on multi-level clustering. In the real society, smurf represents the citizens who disturb social order, and different types of players represent the pyramid structure of social classes. The measures in the game provide references for the construction of a sustainable society.

Determination of Player Types according to Digital Game Playing Preferences: Scale Development and Validation Study

ABSTRACT The aim of this study was to develop a player type determination scale based on Bartle’s taxonomy. In this study, player type determination tests prepared for Bartle’s player types were translated into Turkish by two English experts. The Turkish version of the items was revised by two field experts to best express the point of each item. Next, a scale consisting of 50 items was formed in accordance with the purpose of the study and the level of secondary school students. The scale was administered to 505 secondary school students, and validity and reliability studies were conducted. As a result of a factor analysis, it was decided to remove some items from the test, leading to a measurement instrument of 32 items in total. It was concluded that the scale developed to determine the player type for digital gaming environments was valid and reliable.

Global Convergence for Replicator Dynamics of Repeated Snowdrift Games

To understand the emergence and sustainment of cooperative behavior in interacting collectives, we perform global convergence analysis for replicator dynamics of a large, well-mixed population of individuals playing a repeated snowdrift game with four typical strategies, which are always cooperate (ALLC), tit-for-tat (TFT), suspicious tit-for-tat (STFT), and always defect (ALLD). The dynamical model is a 3-D ordinary differential equation (ODE) system that is parameterized by the payoffs of the base game. Instead of routine searches for evolutionarily stable strategies and sets, we expand our analysis to determining the asymptotic behavior of solution trajectories starting from any initial state, and in particular, show that for the full range of payoffs, every trajectory of the system converges to an equilibrium point. What enables us to achieve such comprehensive results is studying the dynamics of two ratios of the state variables, each of which either monotonically increases or decreases in the half-spaces separated by their corresponding planes. The convergence results highlight two findings. First, the inclusion of TFT- and STFT-players, the two types of conditional strategy players in the game, increases the share of cooperators of the overall population compared to the situation when the population consists of only ALLC and ALLD-players. Second, surprisingly enough, regardless of the payoffs, there always exists a set of initial conditions under which ALLC-players do not vanish in the long run, which does not hold for any of the other three types of players.

Influence of Players' Maximum Running Speed on the Team's Ranking Position at the End of the Spanish LaLiga.

The maximum running speed that a football player can attain during match play has become one of the most popular variables to assess a player’s physical talent. However, the influence of a player’s maximum running speed on football performance has not yet been properly investigated. The aim of this study was to determine the influence of a player’s peak/maximum running speed on the team’s ranking position at the end of a national league. A second aim was to investigate differences in maximum running speed among playing positions. To fulfil this aim, the peak/maximum running speeds of 475 male professional football players were recorded for 38 fixtures of the Spanish first-division league (LaLiga) from the 2017–2018 season (7838 data points). Players’ peak running speeds in each match were assessed with a validated multicamera tracking system and associated software (Mediacoach®). Players’ maximum running speed was established as the fastest running speed they attained during the entire season. Most players (53.5% of the total) had a maximum running speed in the range of 32.0–33.9 km/h, with only three players (0.6%) with a maximum running speed of over 35.0 km/h. Overall, forwards were faster than defenders and both types of players were faster than midfielders (33.03 ± 1.35 > 32.72 ± 1.32 > 32.08 ± 1.63 km/h; p < 0.001). There was no association between teams’ maximum running speed and ranking position at the end of the league (r = −0.356, p = 0.135). The correlations between teams’ maximum speeds and ranking position were low for defenders (r = −0.334, p = 0.163), midfielders (r = 0.125, p = 0.610), and forwards (r = −0.065, p = 0.791). As a result, the variance in the ranking position at the end of the season explained by a team’s maximum speed was of only 7.5%. Finally, as an average for all teams, players’ peak running speeds remained stable at ~30.7 ± 0.6 km/h throughout the whole season. These results suggest that successful and less successful football teams have squads with players able to obtain similar maximum running speeds during match play throughout the season. Hence, players’ maximum running speeds have a poor association with the team’s ranking position at the end of the Spanish professional national league.

The Tripartite Regulation Game of Carbon Financial Products Based on the Prospect Theory

Because of the high information asymmetry of carbon financial products (CFPs), financial institutions infringing on the rights of investors occurred worldwide. However, few studies focused on how to protect investors effectively. In this paper, from the perspective of regulation, we analyze the game relationships among governments, financial institutions, and investors. Following this, the tripartite regulation game of CFPs is further constructed. Meanwhile, centered on heterogeneity and bounded rationality, we divide participants in this game into two types: tough or weak ones, and the strategies for different types of game players are compared based on the prospect theory. Moreover, through discussion of the deterrence equilibrium, challenge equilibrium, and separation equilibrium, the crucial influencing factors of the behavioral strategy are explored separately. Finally, some countermeasures of CFPs are put forward for governments to design appropriate regulation policies.

Optimization of mobile individuals promotes cooperation in social dilemmas

Abstract We study how mobile individuals affect the evolution of cooperation in social dilemmas. In doing so, we consider two types of players. The traditional type simply copies the most successful strategy in its neighborhood in order to improve its future payoff, while the advantageous type moves away in the hope of settling in a better community. We show that the introduction of the advantageous type leads to larger and more compact cooperative clusters in the prisoner’s dilemma game. This in turn facilitates the evolutionary stability of cooperation even under adverse conditions that are characterized by high temptations to defect. We also verify that the average payoff of a community unit remains proportional to the number of cooperators in this community, which hence indicates that the players pursuing mobility to attain a competitive advantage also foster cooperation in their new communities. Another way to communicate this result in the light of the costs associated with moving is to say that optimal mobility, such that yields higher payoffs to the individual who moved and the community as a whole, is similar to the optimization of the allocation of limited resources. We thus hope that these results will shed new light on how to effectively allocate resources and how to optimize mobility for optimal cooperation.

A Bayesian approach to investment in innovation projects with the presence of fake innovators

The paper proposes a game-theoretic model of interaction between investors and innovators, taking into account the existence of so-called “fake” innovators offering knowingly unprofitable projects. The model is a Bayesian non-cooperative, repetitive game with recalculated payments and partly unobservable ex interim player types. It allows quantifying the parameters of the strategy for all player types to find equilibrium solutions. The model describes rational modes for screening “fake” innovators based on adjusting players' probabilistic estimates.

Identifying types in contest experiments

We apply the classifier-Lasso (Su et al. 2016) to detect the presence of latent types in two data sets of previous contest experiments, one that keeps the grouping of contestants fixed over the experiment and one that randomly regroups contestants after each round. Our results suggest that there exist three distinct types of players in both contest regimes. The majority of contestants in fixed groups behaves reciprocal to opponents’ previous choices. A higher share of reciprocators per group is associated to lower average overspending which hints at cooperative attempts. For experiments in which contestants are regrouped, we find a significantly lower share of ‘reciprocators’ and no significant association between the share of reciprocators and average efforts.

The interplay of micro-transaction type and amount of playing in video game evaluations

I examine how the possibility of acquiring different features through in-game purchases (micro-transactions) affect intentions to play and recommend a game. I propose that individuals react more negatively to micro-transactions involving functional rather than aesthetic features. This is because functional, but not aesthetic features, alter the game balance – an essential element of competitive multiplayer games. Further, drawing on the difference between time and money as indicators of preference, I argue that this effect is stronger among those who spend more time playing games, but is not affected by how much money players spend on games. Three online studies (N = 574) with video game players provide converging support for our hypotheses. I conclude with a discussion of balancing game reputation with game revenue in light of different types of players.

On Multidimensional Congestion Games

We introduce multidimensional congestion games, that is, congestion games whose set of players is partitioned into d+1 clusters C0,C1,…,Cd. Players in C0 have full information about all the other participants in the game, while players in Ci, for any 1≤i≤d, have full information only about the members of C0∪Ci and are unaware of all the others. This model has at least two interesting applications: (i) it is a special case of graphical congestion games induced by an undirected social knowledge graph with independence number equal to d, and (ii) it represents scenarios in which players have a type and the level of competition they experience on a resource depends on their type and on the types of the other players using it. We focus on the case in which the cost function associated with each resource is affine and bound the price of anarchy and stability as a function of d with respect to two meaningful social cost functions and for both weighted and unweighted players. We also provide refined bounds for the special case of d=2 in presence of unweighted players.

Corruption as Infrastructure: Rendering the New Saigon Global

AbstractCorruption is regularly treated as a barrier to infrastructure, development and growth. However, in Saigon, corruption itself has become an infrastructure in Vietnam's late‐socialist urban transformation. This infrastructure facilitates not only growth in the form of transnational investment, property speculation and construction, but allows for different kinds of planning and development practice as well. Perceptions about corruption in Vietnam, and in Saigon specifically, shape market and planning practices that structure the terms on which interested parties from abroad and internally speculate upon and ultimately develop urban projects. This is not a static formulation of corruption. Rather, corruption and the various political and policy responses to it constantly shape how brokers, developers and financiers renegotiate how the city becomes a knowable object for investment, legible to the calculations of both risk and reward used by global investors as well as to those who enact the embedded bureaucratic, legal and political practices that create Saigon's built environment. In this article I argue that different definitions and policy responses to corruption in effect create variable ways of seeing the city (as well as modes of being seen) that have an impact on the material realities of the metropolis—the types of connections produced with transnational finance, the legal and regulatory structure under which urbanization unfolds, and the types of players, firms and officials involved.

Bank–fintech partnerships, outsourcing arrangements and the case for a mentorship regime

Amid global competition to build the perfect financial ecosystem, governments worldwide are seeking ways to best harness the potential of new financial technology firms. These fintechs were once seen as ‘disruptors’, potentially displacing established banks and paving the way for more innovative business models. More recently, both types of players have begun to appreciate various forms of collaboration.1 The willingness of consumers to switch from traditional banks to newcomers had probably been overestimated, and this has reinforced the case for collaboration rather than directly enticing customers away from the established players.2 Partnership arrangements between banks and fintech firms may take on various forms, including simple joint ventures, but they may also involve more advanced technology-based ways of integrating new business models or services in the established bank’s portfolio. The main reason for the proliferation of partnership arrangements is the many advantages they bring to both parties. When...

The expected prisoner’s dilemma – With rationally arising cooperation

Currently, there is no satisfying answer to how cooperation arises rationally in a single-play prisoner’s dilemma game with complete information. When player types are known, as well as payoffs and actions, economic analysis through payoff-optimizing computation does not provide a clear path for cooperation. We propose a new form of game–the ‘expected’ game–and illustrate its implications for theory and practice based on the prisoner’s dilemma example. We prove that cooperation can be a rational choice for players in reality in such games defined by a weighted set of payoffs of two or more different reference games.

Understanding online equity funding ecology: a comparison of the greater Los Angeles area and Silicon Valley

Guided by the community ecology perspective and resource dependence theory, this study examines how organizational forms and resources co-influence the financial flow among three types of players: angel investors, venture capital firms and startups. Data from two comparable areas were collected from an online equity funding platform AngelList.com: the greater Los Angeles, and Silicon Valley. This study applies network analysis to demonstrate that the online investment networks in both markets were driven by both commensalism and symbiosis, and they both favored larger ventures. However, distinct patterns were revealed. The Los Angeles market had a higher tendency of the financial flow from angel investors to VC firms, and between angel investors; while the financial flow in the Silicon Valley market was more likely to occur from angel investors and VC firms to startups. Furthermore, the resource signals had different effects on both markets with the investors in Silicon Valley viewing online resources as negative predictors of funding flow. Implications on what value funders bring to ventures and whether online platform offers an alternative for venture investment are provided.

The Use of Game Elements in Higher Education in the Context of Motivating Different Types of Users of Gamified Systems

RESEARCH OBJECTIVE: The main purpose of the article is to select the elements of games that increase the student’s external and internal motivation tailored to the specific type of player he/she represents.&#x0D; THE RESEARCH PROBLEM AND METHODS: The research problem is the issue of motivating students using gamification. The author addresses the issue of preparation of classes that will actually translate into motivation to learn practical skills, but also to develop, pose difficult questions and engage in the learning process. The research is based on the Self-Determination Theory and Marczewski gamification users typology. The basic method used in the presented research is an analysis of a questionnaire conducted among students of the Cracow University of Economics.&#x0D; THE PROCESS OF ARGUMENTATION: The article consists of two main parts. The first presents the concept of gamification and its use in motivating. Second part of the article is divided into three subsections. First of them contains characteristics of different participants types in gamification projects. Second of them presents assumption and research hypotheses, the other one includes analysis of the results and conclusions of the study.&#x0D; RESEARCH RESULTS: Thanks to the conducted research and based on the subject literature, the predispositions of students to accept the use of selected mechanisms known from games were determined. The conducted research confirmed the assumed hypothesis that the legitimacy of using particular elements of gamification depends on the target group of participants. However, the hypothesis of ineffectiveness of the use of elements specific to the type of player was not confirmed.&#x0D; CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: Further research is needed to verify this assumption, e.g. using a gamification project. Due to the limited research sample, the results do not reflect the entire population, but provide a basis for further research on the motivational elements of individual participants.

The Anatomy of Mass Tort and Post-Settlement Litigant Finance in the U.S.

Litigant Third-Party Funding (LTPF), where financial companies advance money on a non-recourse basis to individual plaintiffs, is a growing and increasingly controversial industry in the U.S. This funding made headlines during the NFL concussion litigation with more than 1,000 players reported to have received such advances and with class counsel raising concerns of “predatory lending” with the Court. Policymakers and scholars echo these concerns as they call for regulation of the industry to protect vulnerable consumers. Any regulations, however, should be based on systematic data rather than good intentions or isolated anecdotes. But to date there has been almost no empirical research on the actual practices of the industry. This Article begins to fill that void. Using a unique data set from one of the largest consumer litigation financing firms in the U.S. (“Funder”), we are the first to explore the anatomy of pre-settlement litigant finance in mass tort cases, such as the NFL class action. We are also the first to examine general post-settlement litigant finance in the U.S., which is the type of funding many NFL players were reported to have obtained. Our comprehensive data set includes approximately 225,593 requests for funding from 2001 throughout 2016. With respect to pre-settlement funding, we find that the Funder makes an annual median gross profit of 55% from Mass Tort claims (compared with 60% from Motor Vehicle claims, our control group). We also find that the Funder includes complicated terms in their contracts that make it extremely difficult for clients to understand the actual interest rate they will be eventually be charged. We believe lawmakers should regulate these contracts, banning any unnecessarily complicated provisions and requiring that the effective annual interest rate and total amount due be straightforwardly disclosed. With respect to post-settlement funding, we find that the effective annual interest rate charged and the profit to the Funder are even greater than for post-settlement fundings – 68% compared to 60% for Motor Vehicle claims. This is striking given that post-settlement fundings present virtually no risk to the Funder. Indeed we find that the rate of default in post-settlement cases is close to zero, which means that this category of advance is “non-recourse” on paper but not on the ground. We therefore recommend that funding in post-settlement cases should be subject to consumer protections similar to those usury laws provide for ordinary loans.

Gamification in Corporate Training to Enhance Engagement: An Approach

Engagement in the companies' training programs is a crucial issue for their success. Every company faces the matter in different manners: some enterprises promote mandatory courses or programs; however, they may result not enough effective, due to a low level of motivation that can compromise learning and retention. Other enterprises prefer to adopt voluntary courses or programs, but in this case enrollment and completion depend on many factors: the time that workers can spend on training without compromising their main tasks; the directives of managers; the individual motivation. Another way to face corporate training may exploit gamification to enhance engagement. The authors present the design and implementation of a gamified course of office automation, developed for the employees of a large media company. Our approach attempts to go beyond the well-known triad point-badges-leaderboards, employing also a narrative, the Bartle's taxonomy of player types and the Self-determination theory by Deci and Ryan.

A FinTech-jelenség hagyományos kereskedelmi bankokra gyakorolt hatásának vizsgálata

Az innovativ penzugyi technologiak radikalis valtozasokat eredmenyeznek a penzugyi szolgaltatasok teruleten. A fogyasztoi elvarasok, a digitalis csatornak iranti novekvő kereslet es a penzugyi szektor uj tipusu szereplői a hagyomanyos kereskedelmi bankokat is cselekvesre kesztetik. Jelen cikkben 13 melyinterjun keresztul mutatja be a szerző, hogy a penzugyi szektor szereplői hogyan ertelmezik a FinTech fogalmat es azt, hogy a jelenseg varhatoan milyen hatassal lesz a hagyomanyos kereskedelmi bankok műkodesere es uzleti modelljere. Mindezek mellett, nehany szabalyozoi kihivast is azonosit, amelyek az innovativ fejlesztesek soran akadalyt jelenthetnek mind a bankok, mind pedig a FinTech vallalatok szamara.